Traditional learning management system (LMS) platforms have been a mainstay for organizing and managing corporate training-and-development practices for nearly two decades. They provide learning leaders with an array of features and functions to measure knowledge, track compliance, and ensure organizational readiness. Have yesterday’s tracking systems such as the Sharable Content Object Reference Model (SCORM) and the Aviation Industry Computer-Based Training Committee (AICC) standard kept pace in a learning world that’s more informal, mobile, and collaborative? Do training-and-development professionals require new tools and methods to support their efforts as learning evolves to be more on-demand and predictive?

In this session, you will explore new approaches and technologies that are changing the way learning-and-development teams can design, implement, and deliver next-generation learning initiatives complete with better reporting, deeper analytics, and improved outcomes. You will explore some of the leading and emerging offerings, from simple tools to complex platforms, that are shaping the way organizations can track training and performance support. You will then look at how inexpensive it can be to implement a learning record store (LRS) to manage informal learning interactions and activities. You will gain valuable insights and practical tools to help plan and adopt a flexible learning architecture that combines existing training resources and services with future educational-technology innovations to accelerate organizational performance.

In this session, you will learn:

  • The commercial and open-source options for adding learning-record-store (LRS) services to an existing learning environment
  • How traditional learning management system (LMS) platforms and newer LRS services can coexist in “dual track” scenarios equally supporting legacy alongside emerging learning initiatives
  • The best possible paths to move from an LMS-centric to an LRS-centric learning approach, along with expected obstacles to avoid
  • To identify the range of performance-support sources that comprise the ideal learning data platform and how to tie those sources together
  • How learner profiles serve as the foundation for historical tracking as well as for future predictive learning practices
  • The role data science plays in the way a learning-and-development team can plan and manage an adaptive learning ecosystem

Novice and intermediate designers, developers, project managers, and managers.